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Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method

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  • Christopher Bitter

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  • Gordon Mulligan
  • Sandy Dall’erba

Abstract

Hedonic house price models typically impose a constant price structure on housing characteristics throughout an entire market area. However, there is increasing evidence that the marginal prices of many important attributes vary over space, especially within large markets. In this paper, we compare two approaches to examine spatial heterogeneity in housing attribute prices within the Tucson, Arizona housing market: the spatial expansion method and geographically weighted regression (GWR). Our results provide strong evidence that the marginal price of key housing characteristics varies over space. GWR outperforms the spatial expansion method in terms of explanatory power and predictive accuracy.
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Suggested Citation

  • Christopher Bitter & Gordon Mulligan & Sandy Dall’erba, 2007. "Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method," Journal of Geographical Systems, Springer, vol. 9(1), pages 7-27, April.
  • Handle: RePEc:kap:jgeosy:v:9:y:2007:i:1:p:7-27
    DOI: 10.1007/s10109-006-0028-7
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    Keywords

    Hedonic model; House price; Spatial heterogeneity; Expansion method; Geographically weighted regression; C31; C51; C52; R21; R31;

    JEL classification:

    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General

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